The long-term objective of this research is the development of a general formal model of perceptual categorization and memory, which interrelates performance across a variety of tasks, including classification, identification, and recognition. The present project is organized around the continued development and testing of Nosofsky's (1986, 1987) generalized context model (GCM), which is a highly successful mathematical model of perceptual categorization and recognition. According to the GCM, people represent categories by storing individual exemplars in memory, and make classification and recognition decisions on the basis of similarity comparisons with the stored exemplars. Similarity-scaling techniques are used to represent sets of exemplars in multidimensional psychological spaces. These derived spaces are then used in conjunction with the formal model to quantitatively predict performance in a variety of independent tasks. Although highly successful to date, most previous tests of the GCM have occurred in highly simplified perceptual domains that allowed one to maintain precise control over the fundamental variables of interest. One aim of the present work is to test the model in a much richer, complex domain than has thus far been attempted, and demonstrate its applicability using "ill-defined," natural category structures. A second aim involves the development and testing of dynamic versions of the model, that should allow it to characterize processes of classification learning and changes in category representations as a function of experience. The project involves a continuing interplay among theory development, experimental testing, and modification of theory in line with newly obtained empirical results. Understanding the fundamental processes of categorization and recognition is one of the central goals of research in memory and cognition. Some direct health-related applications of the present work would include providing information about how radiologists make disease classifications on the basis of imperfect information provided in X-ray displays, and constructing mental illness classifications on the basis of reported symptomatology.